Cited 1 time in
A Drone’s 3D Localization and Load Mapping Based on QR Codes for Load Management
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Kang, Tae-Won | - |
| dc.contributor.author | Jung, Jin-Woo | - |
| dc.date.accessioned | 2024-08-08T11:31:56Z | - |
| dc.date.available | 2024-08-08T11:31:56Z | - |
| dc.date.issued | 2024-04 | - |
| dc.identifier.issn | 2504-446X | - |
| dc.identifier.issn | 2504-446X | - |
| dc.identifier.uri | https://scholarworks.dongguk.edu/handle/sw.dongguk/21838 | - |
| dc.description.abstract | The ongoing expansion of the Fourth Industrial Revolution has led to a diversification of drone applications. Among them, this paper focuses on the critical technology required for load management using drones. Generally, when using autonomous drones, global positioning system (GPS) receivers attached to the drones are used to determine the drone’s position. However, GPS integrated into commercially available drones have an error margin on the order of several meters. This paper, proposes a method that uses fixed-size quick response (QR) codes to maintain the error of drone 3D localization within a specific range and enable accurate mapping. In the drone’s 3D localization experiment, the errors were maintained within a specific range, with average errors ranging from approximately 0 to 3 cm, showing minimal differences. During the mapping experiment, the average error between the actual and estimated positions of the QR codes was consistently around 0 to 3 cm. © 2024 by the authors. | - |
| dc.format.extent | 35 | - |
| dc.language | 영어 | - |
| dc.language.iso | ENG | - |
| dc.publisher | MDPI AG | - |
| dc.title | A Drone’s 3D Localization and Load Mapping Based on QR Codes for Load Management | - |
| dc.type | Article | - |
| dc.publisher.location | 스위스 | - |
| dc.identifier.doi | 10.3390/drones8040130 | - |
| dc.identifier.scopusid | 2-s2.0-85191728349 | - |
| dc.identifier.wosid | 001210161700001 | - |
| dc.identifier.bibliographicCitation | Drones, v.8, no.4, pp 1 - 35 | - |
| dc.citation.title | Drones | - |
| dc.citation.volume | 8 | - |
| dc.citation.number | 4 | - |
| dc.citation.startPage | 1 | - |
| dc.citation.endPage | 35 | - |
| dc.type.docType | Article | - |
| dc.description.isOpenAccess | Y | - |
| dc.description.journalRegisteredClass | scie | - |
| dc.description.journalRegisteredClass | scopus | - |
| dc.relation.journalResearchArea | Remote Sensing | - |
| dc.relation.journalWebOfScienceCategory | Remote Sensing | - |
| dc.subject.keywordAuthor | drone | - |
| dc.subject.keywordAuthor | load management | - |
| dc.subject.keywordAuthor | localization | - |
| dc.subject.keywordAuthor | mapping | - |
| dc.subject.keywordAuthor | quick response (QR) code | - |
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